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5 Mistakes businessmen make when they work with Big Data
5 Mistakes businessmen make when they work with Big Data
5 Mistakes businessmen make when they work with Big Data
 

Big data has launched a boom industry in data analytics and science. Investing in big data is all the rage right now. But as with many topics that become buzz worthy, its core values often get lost in the hype. Big corporations and small startups alike are making a big deal out of analysing big data.

Here are the biggest business mistakes – of varying degrees, but all mammoth whoppers.

  1. Misunderstanding the System & Data: The biggest problem with this is that companies don’t always know how to leverage it fully. The first step to deploying big data is whittling down what needs analysis. Companies do not have a qualified Data Scientist or someone who can interpret or map/reduce the proper dimensions of data. Instead they rely on non-qualified personnel to interpret data. The improper analysis of data can be very harmful to a company.

  2. Crowd Mentality: As the Big Data is the top of SEO many people just misunderstand it. The need for going for big data must be studied very carefully and patiently – there is no plug and play recipe around, no one size fit all is available. And surely, it may not fit every organization, but again, it is about understanding the reason why it should be done in the first place. With understanding of the vision and/or the goal comes the proper planning that helps identify the right people, the right process, and the right technology for big data.

  3. Avoiding to Track Time & Cost: Many companies don’t invest enough in time tracking and cost accounting. Especially for a service-based business, having the proper time-tracking tools for true cost accounting is very important to be better able to tell true margins across all offerings. This information can be used to increase efficiency and profitability.

  4. One-stop-shopping: Many organizations treat Big Data as a one-time investment and expect to run it flawless after the initial implementation. This is one of the more common mistakes. While implementing a BigData solution, you need to keep track of the progress and make tweaks. Even after implementation, you need to modify it in accordance to your changing business needs and goals.

  5. No Strategy: The final and probably the biggest flaw is to not have a strategy at all. Organizations still find it hard to come out of the “Excel culture” of manually entering, storing and analysing data. It is not only time-consuming and obsolete but is error-prone and least effective in this fast-paced business environment. Having a poorly implemented strategy is equally dangerous as having no strategy. It invites unwanted costs, complicate the entire functions and add silos.

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